{"entity":{"id":"ood-detection","kind":"term","name":"Out-of-distribution detection (Mahalanobis guard)","aka":["out-of-distribution","OOD","OOD detection","out-of-distribution detection","OOD guard","Mahalanobis distance","Mahalanobis guard","ManifoldGuard","off-manifold input","refused prediction"],"tldr":"Out-of-distribution detection flags an input that does not look like anything the model was trained on, so the model can refuse to predict instead of guessing; the Mahalanobis distance from the training cloud is the simplest such guard.","summary":"Anomaly detection identifies rare items that deviate significantly from the majority of the data (Wikipedia). The Mahalanobis distance measures how far a point lies from a distribution, accounting for its covariance (Wikipedia); computed in PCA space against the training cohort it gives a threshold beyond which a sample (a new platform, a different tissue, a corrupted file) is declared off-manifold and the prediction withheld. Passing the guard is necessary, not sufficient: an in-distribution sample can still yield an unstable prediction.","asOf":"2026-09-24","wikipedia":"https://en.wikipedia.org/wiki/Anomaly_detection","links":[{"label":"Wikipedia: Mahalanobis distance","url":"https://en.wikipedia.org/wiki/Mahalanobis_distance"},{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Anomaly_detection"}],"tags":["cansim-terms"],"related":["cancer-ai-vocabulary"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["domain-adaptation","uncertainty-quantification","pca","bootstrap"],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":["Listed in the CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme; CanSim page path /terms/ood-detection."],"provenance":{"editedBy":"OnCo CanSim terms wave (Wikipedia summaries, standards and project pages, GDC and FDA pages, Europe PMC)","editedOn":"2026-09-24","note":"CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme"},"category":"Methods and models"},"route":"/terms/ood-detection/","neighbours":{"term":[{"id":"bootstrap","kind":"term","name":"Bootstrap resampling","route":"/terms/bootstrap/"},{"id":"cancer-ai-vocabulary","kind":"term","name":"Cancer AI vocabulary (CanSim terms map)","route":"/terms/cancer-ai-vocabulary/"},{"id":"conformal-prediction","kind":"term","name":"Conformal prediction","route":"/terms/conformal-prediction/"},{"id":"domain-adaptation","kind":"term","name":"Domain shift and domain adaptation (cell line to patient)","route":"/terms/domain-adaptation/"},{"id":"pca","kind":"term","name":"Principal component analysis (PCA) as a feature compressor","route":"/terms/pca/"},{"id":"uncertainty-quantification","kind":"term","name":"Uncertainty quantification and confidence gates","route":"/terms/uncertainty-quantification/"}]}}